Calibrated imaging radar polarimetry: technique, examples, and applications

Zebker, H. A.; Zyl, J.J. van; Durden, Stephen L.; Norikane, L.

doi:10.1109/36.101373

Cited by 59 publications

(15 citation statements)

References 15 publications

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“…Two important examples of results are reported by Zebker et al (1991) and Chauhan et al (1991). Zebker et al show (To values measured over a coniferous forest (Mt Shasta) and a tropical rain forest (Belize).…”

Section: Comparison With Experimental Resultsmentioning

confidence: 85%

Interpretation and model analysis of MAESTRO 1 Flevoland data

Ferrazzoli

Guerriero

1994

International Journal of Remote Sensing

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A model, based on the Radiative Transfer Theory and the Matrix Doubling algorithm, is tested with agricultural and forest radar returns measured by the JPL AIRSAR sensor over the Flevoland site (The Netherlands) at P, L and C bands.The test is generally valid, although some discrepancies are noted in the absolute P band values of U O and not all the input parameters were obtainable from ground measurements. The model is also used to interpret the experimental results and to estimate the relative importance of the different scattering contributions.

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Section: Comparison With Experimental Resultsmentioning

confidence: 85%

Interpretation and model analysis of MAESTRO 1 Flevoland data

Ferrazzoli

Guerriero

1994

International Journal of Remote Sensing

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“…The values of k and α relate to the channel imbalance and the 11 . An overall gain factor, r 22 t 22 , has been dropped, so absolute radiometric calibration is not considered.…”

Section: Calibration Equationsmentioning

confidence: 99%

“…The direct effect of k is on the co-polarization returns and their correlations. Traditionally, an in-scene trihedral corner reflector fixes both the phase and amplitude of k [6]- [11]. Alternatively, either theoretical or empirical models of presumed scattering mechanisms in the scene can be employed to set the S HH /S VV ratio.…”

Section: Scheme Of Solving Kmentioning

confidence: 99%

A Modified Method for Polarimetric Sar Calibration Algorithm

Liao

2013

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Present fully polarimetric synthetic aperture radar (SAR) systems often update calibration techniques to further enhance the accuracy to the polarimetric data. In this paper, we propose a modified method to estimate the value of crosstalk based on the corrected observed value. Since Ainsworth calibration algorithm firstly set the value of k to be one. And the value of k relates to the copolarization channel imbalance .We consider the effects of value of k and analyze it. Through comparison to crosstalk results between the stimulated parameters and the estimated parameters, we assume high co-polarization channel imbalance will be obviously to affect crosstalk results. Then, used covariance observation value of the initial value of k rewrites the model to solve related parameters. And crosstalk parameter is calculated by the same iterative method. To verify the effect of the modified calibration method, this letter compares the accuracy of the two methods using the simulated polarimetric SAR data and Chinese airborne X-band polarimetric SAR data. The results confirm that the modified method tends to get more accurate crosstalk results.

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“…Many algorithms have been developed to classify natural media using polarimetric synthetic aperture radar (POLSAR) data [1][2][3][4][5]. Several approaches were derived to directly relate some basic characteristics of the targets to elements of the polarimetric covariance matrix [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Dual Frequency Polarimetric SAR Data Classification and Analysis

Ferro-Famil¹,

Pottier²

2001

PIER

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Abstract-In this paper, we introduce a new classification scheme for dual frequency polarimetric SAR data sets. A (6 × 6) polarimetric coherency matrix is defined to simultaneously take into account the full polarimetric information from both images. This matrix is composed of the two coherency matrices and their cross-correlation. A decomposition theorem is applied to both images to obtain 64 initial clusters based on their scattering characteristics. The data sets are then classified by an iterative algorithm based on a complex Wishart density function of the 6 by 6 matrix. A class number reduction technique is then applied on the 64 resulting clusters to improve the efficiency of the interpretation and representation of each class characteristics. An alternative technique is also proposed which introduces the polarimetric cross-correlation information to refine the results of classification to a small number of clusters using the conditional probability of the crosscorrelation matrix. The analysis of the resulting clusters is realized by determining the rigorous change in polarimetric properties from one image to the other. The polarimetric variations are parameterized by 8 real coefficients derived from the decomposition of a special unitary operator on the Gell-Mann basis. These classification and analysis schemes are applied to full polarimetric P, L, and C bands SAR images of the Nezer forest acquired by NASA/JPL AIRSAR sensor (1989).

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Calibrated imaging radar polarimetry: technique, examples, and applications

Cited by 59 publications

References 15 publications

Interpretation and model analysis of MAESTRO 1 Flevoland data

Interpretation and model analysis of MAESTRO 1 Flevoland data

A Modified Method for Polarimetric Sar Calibration Algorithm

Dual Frequency Polarimetric SAR Data Classification and Analysis

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